UpdatePhi: Update phi.

In NestedCategBayesImpute: Modeling, Imputing and Generating Synthetic Versions of Nested Categorical Data in the Presence of Impossible Combinations

Description

Update phi – the matrix of posterior samples for the individual-level probabilities for each individual-level variable by each pair of group-level and individual-level latent classes – when the weighting/capping option is not used.

Usage

UpdatePhi(data, M_all, FF, SS, d, maxd)

Arguments

data	Data matrix for the individual-level data from both the original data and the sampled impossible households.
M_all	A vector of both the household-level and individual-level latent class indexes for all households both in the original data and the sampled impossible households.
FF	Maximum number of household-level latent classes allowed.
SS	Maximum number of individual-level latent classes allowed.
d	A vector for the number of levels of each individual-level variable.
maxd	Maximum value in d.

Details

Function for obtaining a posterior sample of phi when the weighting/capping option is not used.

Value

Updated (posterior) value for phi based on the corresponding full conditional distribution.

Author(s)

Quanli Wang

NestedCategBayesImpute documentation built on May 2, 2019, 3:26 p.m.